Pandas Profiling Report

Dataset statistics

Number of variables	13
Number of observations	299
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	30.5 KiB
Average record size in memory	104.4 B

Variable types

Numeric	7
Categorical	6

Alerts

`time` is highly correlated with `DEATH_EVENT`	High correlation
`DEATH_EVENT` is highly correlated with `time`	High correlation
`time` is highly correlated with `DEATH_EVENT`	High correlation
`DEATH_EVENT` is highly correlated with `time`	High correlation
`age` is highly correlated with `diabetes` and 2 other fields	High correlation
`anaemia` is highly correlated with `diabetes` and 4 other fields	High correlation
`creatinine_phosphokinase` is highly correlated with `high_blood_pressure` and 3 other fields	High correlation
`diabetes` is highly correlated with `age` and 5 other fields	High correlation
`ejection_fraction` is highly correlated with `high_blood_pressure` and 3 other fields	High correlation
`high_blood_pressure` is highly correlated with `anaemia` and 5 other fields	High correlation
`platelets` is highly correlated with `sex` and 2 other fields	High correlation
`serum_creatinine` is highly correlated with `sex` and 1 other fields	High correlation
`serum_sodium` is highly correlated with `sex` and 2 other fields	High correlation
`sex` is highly correlated with `age` and 9 other fields	High correlation
`smoking` is highly correlated with `age` and 9 other fields	High correlation
`time` is highly correlated with `DEATH_EVENT`	High correlation
`DEATH_EVENT` is highly correlated with `anaemia` and 8 other fields	High correlation
`ejection_fraction` is highly correlated with `serum_creatinine` and 1 other fields	High correlation
`serum_creatinine` is highly correlated with `ejection_fraction`	High correlation
`sex` is highly correlated with `smoking`	High correlation
`smoking` is highly correlated with `sex`	High correlation
`time` is highly correlated with `DEATH_EVENT`	High correlation
`DEATH_EVENT` is highly correlated with `ejection_fraction` and 1 other fields	High correlation

Reproduction

Analysis started	2021-11-17 00:27:15.764230
Analysis finished	2021-11-17 00:27:35.851358
Duration	20.09 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

age
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	47
Distinct (%)	15.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	60.83389298

Minimum	40
Maximum	95
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.5 KiB

Quantile statistics

Minimum	40
5-th percentile	42.9
Q1	51
median	60
Q3	70
95-th percentile	82
Maximum	95
Range	55
Interquartile range (IQR)	19

Descriptive statistics

Standard deviation	11.89480907
Coefficient of variation (CV)	0.1955293093
Kurtosis	-0.184870532
Mean	60.83389298
Median Absolute Deviation (MAD)	10
Skewness	0.4230619067
Sum	18189.334
Variance	141.4864829
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=47)

Value	Count	Frequency (%)
60	33	11.0%
50	27	9.0%
65	26	8.7%
70	25	8.4%
45	19	6.4%
55	17	5.7%
75	11	3.7%
53	10	3.3%
58	10	3.3%
63	8	2.7%
Other values (37)	113	37.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
40	7	2.3%
41	1	0.3%
42	7	2.3%
43	1	0.3%
44	2	0.7%
45	19	6.4%
46	3	1.0%
47	1	0.3%
48	2	0.7%
49	4	1.3%

Value	Count	Frequency (%)
95	2	0.7%
94	1	0.3%
90	3	1.0%
87	1	0.3%
86	1	0.3%
85	6	2.0%
82	3	1.0%
81	1	0.3%
80	7	2.3%
79	1	0.3%

anaemia
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	2.5 KiB

0	170
1	129

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	170	56.9%
1	129	43.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	170	56.9%
1	129	43.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

creatinine_phosphokinase
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	208
Distinct (%)	69.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	581.8394649

Minimum	23
Maximum	7861
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.5 KiB

Quantile statistics

Minimum	23
5-th percentile	59
Q1	116.5
median	250
Q3	582
95-th percentile	2263
Maximum	7861
Range	7838
Interquartile range (IQR)	465.5

Descriptive statistics

Standard deviation	970.2878807
Coefficient of variation (CV)	1.667621293
Kurtosis	25.1490462
Mean	581.8394649
Median Absolute Deviation (MAD)	182
Skewness	4.463110085
Sum	173970
Variance	941458.5715
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
582	47	15.7%
66	4	1.3%
129	4	1.3%
231	3	1.0%
69	3	1.0%
68	3	1.0%
84	3	1.0%
115	3	1.0%
59	3	1.0%
60	3	1.0%
Other values (198)	223	74.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
23	1	0.3%
30	1	0.3%
47	3	1.0%
52	1	0.3%
53	1	0.3%
54	1	0.3%
55	1	0.3%
56	2	0.7%
57	1	0.3%
58	1	0.3%

Value	Count	Frequency (%)
7861	1	0.3%
7702	1	0.3%
5882	1	0.3%
5209	1	0.3%
4540	1	0.3%
3966	1	0.3%
3964	1	0.3%
2794	1	0.3%
2695	1	0.3%
2656	1	0.3%

diabetes
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	2.5 KiB

0	174
1	125

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	174	58.2%
1	125	41.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	174	58.2%
1	125	41.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ejection_fraction
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	17
Distinct (%)	5.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	38.08361204

Minimum	14
Maximum	80
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.5 KiB

Quantile statistics

Minimum	14
5-th percentile	20
Q1	30
median	38
Q3	45
95-th percentile	60
Maximum	80
Range	66
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	11.83484074
Coefficient of variation (CV)	0.3107594082
Kurtosis	0.04140935982
Mean	38.08361204
Median Absolute Deviation (MAD)	8
Skewness	0.5553827517
Sum	11387
Variance	140.0634554
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
35	49	16.4%
38	40	13.4%
40	37	12.4%
25	36	12.0%
30	34	11.4%
60	31	10.4%
50	21	7.0%
45	20	6.7%
20	18	6.0%
55	3	1.0%
Other values (7)	10	3.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
14	1	0.3%
15	2	0.7%
17	2	0.7%
20	18	6.0%
25	36	12.0%
30	34	11.4%
35	49	16.4%
38	40	13.4%
40	37	12.4%
45	20	6.7%

Value	Count	Frequency (%)
80	1	0.3%
70	1	0.3%
65	1	0.3%
62	2	0.7%
60	31	10.4%
55	3	1.0%
50	21	7.0%
45	20	6.7%
40	37	12.4%
38	40	13.4%

high_blood_pressure
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	2.5 KiB

0	194
1	105

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	194	64.9%
1	105	35.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	194	64.9%
1	105	35.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

platelets
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	176
Distinct (%)	58.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	263358.0293

Minimum	25100
Maximum	850000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.5 KiB

Quantile statistics

Minimum	25100
5-th percentile	131800
Q1	212500
median	262000
Q3	303500
95-th percentile	422500
Maximum	850000
Range	824900
Interquartile range (IQR)	91000

Descriptive statistics

Standard deviation	97804.23687
Coefficient of variation (CV)	0.3713736663
Kurtosis	6.209254515
Mean	263358.0293
Median Absolute Deviation (MAD)	44000
Skewness	1.462320838
Sum	78744050.75
Variance	9565668749
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
263358.03	25	8.4%
221000	4	1.3%
279000	4	1.3%
271000	4	1.3%
305000	4	1.3%
226000	4	1.3%
228000	4	1.3%
235000	4	1.3%
237000	4	1.3%
255000	4	1.3%
Other values (166)	238	79.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
25100	1	0.3%
47000	1	0.3%
51000	1	0.3%
62000	1	0.3%
70000	1	0.3%
73000	1	0.3%
75000	1	0.3%
87000	1	0.3%
105000	1	0.3%
119000	1	0.3%

Value	Count	Frequency (%)
850000	1	0.3%
742000	1	0.3%
621000	1	0.3%
543000	1	0.3%
533000	1	0.3%
507000	1	0.3%
504000	1	0.3%
497000	1	0.3%
481000	1	0.3%
461000	1	0.3%

serum_creatinine
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	40
Distinct (%)	13.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.393879599

Minimum	0.5
Maximum	9.4
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.5 KiB

Quantile statistics

Minimum	0.5
5-th percentile	0.7
Q1	0.9
median	1.1
Q3	1.4
95-th percentile	3
Maximum	9.4
Range	8.9
Interquartile range (IQR)	0.5

Descriptive statistics

Standard deviation	1.034510064
Coefficient of variation (CV)	0.7421803613
Kurtosis	25.82823866
Mean	1.393879599
Median Absolute Deviation (MAD)	0.2
Skewness	4.455995882
Sum	416.77
Variance	1.070211073
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=40)

Value	Count	Frequency (%)
1	50	16.7%
1.1	32	10.7%
0.9	32	10.7%
1.2	24	8.0%
0.8	24	8.0%
1.3	20	6.7%
0.7	19	6.4%
1.18	11	3.7%
1.4	9	3.0%
1.7	9	3.0%
Other values (30)	69	23.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.5	1	0.3%
0.6	4	1.3%
0.7	19	6.4%
0.75	1	0.3%
0.8	24	8.0%
0.9	32	10.7%
1	50	16.7%
1.1	32	10.7%
1.18	11	3.7%
1.2	24	8.0%

Value	Count	Frequency (%)
9.4	1	0.3%
9	1	0.3%
6.8	1	0.3%
6.1	1	0.3%
5.8	1	0.3%
5	1	0.3%
4.4	1	0.3%
4	1	0.3%
3.8	1	0.3%
3.7	1	0.3%

serum_sodium
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	27
Distinct (%)	9.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	136.6254181

Minimum	113
Maximum	148
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.5 KiB

Quantile statistics

Minimum	113
5-th percentile	130
Q1	134
median	137
Q3	140
95-th percentile	144
Maximum	148
Range	35
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.412477284
Coefficient of variation (CV)	0.03229616675
Kurtosis	4.119712008
Mean	136.6254181
Median Absolute Deviation (MAD)	3
Skewness	-1.048136016
Sum	40851
Variance	19.46995578
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=27)

Value	Count	Frequency (%)
136	40	13.4%
137	38	12.7%
140	35	11.7%
134	32	10.7%
138	23	7.7%
139	22	7.4%
135	16	5.4%
132	14	4.7%
141	12	4.0%
142	11	3.7%
Other values (17)	56	18.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
113	1	0.3%
116	1	0.3%
121	1	0.3%
124	1	0.3%
125	1	0.3%
126	1	0.3%
127	3	1.0%
128	2	0.7%
129	2	0.7%
130	9	3.0%

Value	Count	Frequency (%)
148	1	0.3%
146	1	0.3%
145	9	3.0%
144	5	1.7%
143	3	1.0%
142	11	3.7%
141	12	4.0%
140	35	11.7%
139	22	7.4%
138	23	7.7%

sex
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	2.5 KiB

1	194
0	105

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	194	64.9%
0	105	35.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	194	64.9%
0	105	35.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

smoking
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	2.5 KiB

0	203
1	96

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	203	67.9%
1	96	32.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	203	67.9%
1	96	32.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

time
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	148
Distinct (%)	49.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	130.2608696

Minimum	4
Maximum	285
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.5 KiB

Quantile statistics

Minimum	4
5-th percentile	12.9
Q1	73
median	115
Q3	203
95-th percentile	250
Maximum	285
Range	281
Interquartile range (IQR)	130

Descriptive statistics

Standard deviation	77.61420795
Coefficient of variation (CV)	0.5958367099
Kurtosis	-1.212047967
Mean	130.2608696
Median Absolute Deviation (MAD)	71
Skewness	0.1278026456
Sum	38948
Variance	6023.965276
Monotonicity	Increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
250	7	2.3%
187	7	2.3%
10	6	2.0%
186	6	2.0%
107	6	2.0%
30	5	1.7%
209	5	1.7%
244	5	1.7%
95	5	1.7%
214	5	1.7%
Other values (138)	242	80.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4	1	0.3%
6	1	0.3%
7	2	0.7%
8	2	0.7%
10	6	2.0%
11	2	0.7%
12	1	0.3%
13	1	0.3%
14	2	0.7%
15	2	0.7%

Value	Count	Frequency (%)
285	1	0.3%
280	1	0.3%
278	1	0.3%
271	1	0.3%
270	2	0.7%
258	2	0.7%
257	1	0.3%
256	2	0.7%
250	7	2.3%
247	1	0.3%

DEATH_EVENT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	2.5 KiB

0	203
1	96

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	203	67.9%
1	96	32.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	203	67.9%
1	96	32.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	age	anaemia	creatinine_phosphokinase	diabetes	ejection_fraction	high_blood_pressure	platelets	serum_creatinine	serum_sodium	sex	smoking	time	DEATH_EVENT
0	75.0	0	582	0	20	1	265000.00	1.9	130	1	0	4	1
1	55.0	0	7861	0	38	0	263358.03	1.1	136	1	0	6	1
2	65.0	0	146	0	20	0	162000.00	1.3	129	1	1	7	1
3	50.0	1	111	0	20	0	210000.00	1.9	137	1	0	7	1
4	65.0	1	160	1	20	0	327000.00	2.7	116	0	0	8	1
5	90.0	1	47	0	40	1	204000.00	2.1	132	1	1	8	1
6	75.0	1	246	0	15	0	127000.00	1.2	137	1	0	10	1
7	60.0	1	315	1	60	0	454000.00	1.1	131	1	1	10	1
8	65.0	0	157	0	65	0	263358.03	1.5	138	0	0	10	1
9	80.0	1	123	0	35	1	388000.00	9.4	133	1	1	10	1

Last rows

	age	anaemia	creatinine_phosphokinase	diabetes	ejection_fraction	high_blood_pressure	platelets	serum_creatinine	serum_sodium	sex	smoking	time
289	90.0	1	337	0	38	0	390000.0	0.9	144	0	0	256
290	45.0	0	615	1	55	0	222000.0	0.8	141	0	0	257
291	60.0	0	320	0	35	0	133000.0	1.4	139	1	0	258
292	52.0	0	190	1	38	0	382000.0	1.0	140	1	1	258
293	63.0	1	103	1	35	0	179000.0	0.9	136	1	1	270
294	62.0	0	61	1	38	1	155000.0	1.1	143	1	1	270
295	55.0	0	1820	0	38	0	270000.0	1.2	139	0	0	271
296	45.0	0	2060	1	60	0	742000.0	0.8	138	0	0	278
297	45.0	0	2413	0	38	0	140000.0	1.4	140	1	1	280
298	50.0	0	196	0	45	0	395000.0	1.6	136	1	1	285

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows